UNT Libraries - 291 Matching Results

Search Results

Results: 1 - 50 next
A Platform for Aligning Academic Assessments to Industry and Federal Job Postings
The proposed tool will provide users with a platform to access a side-by-side comparison of classroom assessment and job posting requirements. Using techniques and methodologies from NLP, machine learning, data analysis, and data mining: the employed algorithm analyzes job postings and classroom assessments, extracts and classifies skill units within, then compares sets of skills from different input volumes. This effectively provides a predicted alignment between academic and career sources, both federal and industrial. The compilation of tool results indicates an overall accuracy score of 82%, and an alignment score of only 75.5% between the input assessments and overall job postings. These results describe that the 50 UNT assessments and 5,000 industry and federal job postings examined, demonstrate a compatibility (alignment) of 75.5%; and, that this measure was calculated using a tool operating at an 82% precision rate.
Evaluating Stack Overflow Usability Posts in Conjunction with Usability Heuristics
This thesis explores the critical role of usability in software development and uses usability heuristics as a cost-effective and efficient method for evaluating various software functions and interfaces. With the proliferation of software development in the modern digital age, developing user-friendly interfaces that meet the needs and preferences of users has become a complex process. Usability heuristics, a set of guidelines based on principles of human-computer interaction, provide a starting point for designers to create intuitive, efficient, and easy-to-use interfaces that provide a seamless user experience. The study uses Jakob Nieson's ten usability heuristics to evaluate the usability of Stack Overflow posts, a popular Q\&A website for developers. Through the analysis of 894 posts related to usability, the study identifies common usability problems faced by users and developers, providing valuable insights into the effectiveness of usability guidelines in software development practice. The research findings emphasize the need for ongoing evaluation and improvement of software interfaces to ensure a seamless user experience. The thesis concludes by highlighting the potential of usability heuristics in guiding the design of user-friendly software interfaces and improving the overall user experience in software development.
Autonomic Zero Trust Framework for Network Protection
With the technological improvements, the number of Internet connected devices is increasing tremendously. We also observe an increase in cyberattacks since the attackers want to use all these interconnected devices for malicious intention. Even though there exist many proactive security solutions, it is not practical to run all the security solutions on them as they have limited computational resources and even battery operated. As an alternative, Zero Trust Architecture (ZTA) has become popular is because it defines boundaries and requires to monitor all events, configurations, and connections and evaluate them to enforce rejecting by default and accepting only if they are known and accepted as well as applies a continuous trust evaluation. In addition, we need to be able to respond as quickly as possible, which cannot be managed by human interaction but through autonomous computing paradigm. Therefore, in this work, we propose a framework that would implement ZTA using autonomous computing paradigm. The proposed solution, Autonomic ZTA Management Engine (AZME) framework, focusing on enforcing ZTA on network, uses a set of sensors to monitor a network, a set of user-defined policies to define which actions to be taken (through controller). We have implemented a Python prototype as a proof-of-concept that checks network packets and enforce ZTA by checking the individual source and destination based on the given policies and continuously evaluate the trust of connections. If an unaccepted connection is made, it can block the connection by creating firewall rule at runtime.
A Method of Combining GANs to Improve the Accuracy of Object Detection on Autonomous Vehicles
As the technology in the field of computer vision becomes more and more mature, the autonomous vehicles have achieved rapid developments in recent years. However, the object detection and classification tasks of autonomous vehicles which are based on cameras may face problems when the vehicle is driving at a relatively high speed. One is that the camera will collect blurred photos when driving at high speed which may affect the accuracy of deep neural networks. The other is that small objects far away from the vehicle are difficult to be recognized by networks. In this paper, we present a method to combine two kinds of GANs to solve these problems. We choose DeblurGAN as the base model to remove blur in images. SRGAN is another GAN we choose for solving small object detection problems. Due to the total time of these two are too long, we still do the model compression on it to make it lighter. Then we use the Yolov4 to do the object detection. Finally we do the evaluation of the whole model architecture and proposed a model version 2 based on DeblurGAN and ESPCN which is faster than previous one but the accuracy may be lower.
Red Door: Firewall Based Access Control in ROS
ROS is a set of computer operating system framework designed for robot software development, and Red Door, a lightweight software firewall that serves the ROS, is intended to strengthen its security. ROS has many flaws in security, such as clear text transmission of data, no authentication mechanism, etc. Red Door can achieve identity verification and access control policy with a small performance loss, all without modifying the ROS source code, to ensure the availability and authentication of ROS applications to the greatest extent.
Towards a Unilateral Sensing System for Detecting Person-to-Person Contacts
The contact patterns among individuals can significantly affect the progress of an infectious outbreak within a population. Gathering data about these interaction and mixing patterns is essential to assess computational modeling of infectious diseases. Various self-report approaches have been designed in different studies to collect data about contact rates and patterns. Recent advances in sensing technology provide researchers with a bilateral automated data collection devices to facilitate contact gathering overcoming the disadvantages of previous approaches. In this study, a novel unilateral wearable sensing architecture has been proposed that overcome the limitations of the bi-lateral sensing. Our unilateral wearable sensing system gather contact data using hybrid sensor arrays embedded in wearable shirt. A smartphone application has been used to transfer the collected sensors data to the cloud and apply deep learning model to estimate the number of human contacts and the results are stored in the cloud database. The deep learning model has been developed on the hand labelled data over multiple experiments. This model has been tested and evaluated, and these results were reported in the study. Sensitivity analysis has been performed to choose the most suitable image resolution and format for the model to estimate contacts and to analyze the model's consumption of computer resources.
Encrypted Collaborative Editing Software
Cloud-based collaborative editors enable real-time document processing via remote connections. Their common application is to allow Internet users to collaboratively work on their documents stored in the cloud, even if these users are physically a world apart. However, this convenience comes at a cost in terms of user privacy. Hence, the growth of popularity of cloud computing application stipulates the growth in importance of cloud security. A major concern with the cloud is who has access to user data. In order to address this issue, various third-party services offer encryption mechanisms for protection of the user data in the case of insider attacks or data leakage. However, these services often only encrypt data-at-rest, leaving the data which is being processed potentially vulnerable. The purpose of this study is to propose a prototype software system that encrypts collaboratively edited data in real-time, preserving the user experience similar to that of, e.g., Google Docs.
Determining Event Outcomes from Social Media
An event is something that happens at a time and location. Events include major life events such as graduating college or getting married, and also simple day-to-day activities such as commuting to work or eating lunch. Most work on event extraction detects events and the entities involved in events. For example, cooking events will usually involve a cook, some utensils and appliances, and a final product. In this work, we target the task of determining whether events result in their expected outcomes. Specifically, we target cooking and baking events, and characterize event outcomes into two categories. First, we distinguish whether something edible resulted from the event. Second, if something edible resulted, we distinguish between perfect, partial and alternative outcomes. The main contributions of this thesis are a corpus of 4,000 tweets annotated with event outcome information and experimental results showing that the task can be automated. The corpus includes tweets that have only text as well as tweets that have text and an image.
A Study on Usability of Mobile Software Targeted at Elderly People in China
With the rapid development of mobile device technology, smartphones are now not only the tool for young people but also for elderly people. However, the complicated steps of interacting with smartphones are stopping them from having a good user experience. One of the reasons is that application designers do not take consideration of the user group of elderly people. Our pilot survey shows that most elderly people lack the skills required to use a smartphone without obstacles, like typing. We also conducted an experiment with 8 participants that targeting on the usability of a daily used application, Contact List (CL), and based on a Chinese language system. We developed an android application that proposed a new method of showing the contact list according to the language usage of Chinese for this study. By asking participants to finish the same tasks on the traditional CL applications on their phones or on our application and observing their operations, we obtained useful feedback in terms of usability issues. Our experiment also tried to find out whether the method we proposed in the new application can lead to a better user experience for elderly people.
Managing Access during Employee Separation using Blockchain Technology
On-boarding refers to bringing in an employee to a company and granting access to new hires. However, a person may go through different stages of employment, hold different jobs by the same employer and have different levels of information access during the employment duration. A shared services organization may have either limited or wide-spread access within certain groups. Off-boarding implies the removal of access of information or physical devices such as keys, computers or mobile devices when the employee leaves. Off-boarding is the management of the separation an employee from an institution. Many organizations use different steps that constitute the off-boarding process. Incomplete tracking of an employee's access is a security risk and can lead to unintended exposure of company information and assets. Blockchain technology combines blocks of information together using a cryptographic algorithm based on the existing previous block and is verified by the peers in the blockchain network. This process creates an immutable record of employee system access providing an audit trail of access for any point in time to ensure that all access permissions can be removed once employment ends. This project proposes using blockchain technology to consolidate information across disparate groups, and to automate access removal to improve the employee off-boarding process.
BC Framework for CAV Edge Computing
Edge computing and CAV (Connected Autonomous Vehicle) fields can work as a team. With the short latency and high responsiveness of edge computing, it is a better fit than cloud computing in the CAV field. Moreover, containerized applications are getting rid of the annoying procedures for setting the required environment. So that deployment of applications on new machines is much more user-friendly than before. Therefore, this paper proposes a framework developed for the CAV edge computing scenario. This framework consists of various programs written in different languages. The framework uses Docker technology to containerize these applications so that the deployment could be simple and easy. This framework consists of two parts. One is for the vehicle on-board unit, which exposes data to the closest edge device and receives the output generated by the edge device. Another is for the edge device, which is responsible for collecting and processing big load of data and broadcasting output to vehicles. So the vehicle does not need to perform the heavyweight tasks that could drain up the limited power.
Biomedical Semantic Embeddings: Using Hybrid Sentences to Construct Biomedical Word Embeddings and its Applications
Word embeddings is a useful method that has shown enormous success in various NLP tasks, not only in open domain but also in biomedical domain. The biomedical domain provides various domain specific resources and tools that can be exploited to improve performance of these word embeddings. However, most of the research related to word embeddings in biomedical domain focuses on analysis of model architecture, hyper-parameters and input text. In this paper, we use SemMedDB to design new sentences called `Semantic Sentences'. Then we use these sentences in addition to biomedical text as inputs to the word embedding model. This approach aims at introducing biomedical semantic types defined by UMLS, into the vector space of word embeddings. The semantically rich word embeddings presented here rivals state of the art biomedical word embedding in both semantic similarity and relatedness metrics up to 11%. We also demonstrate how these semantic types in word embeddings can be utilized.
Enhanced Approach for the Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using CNN
Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. To achieve the therapeutic goals of UC, which are to first induce and then maintain disease remission, doctors need to evaluate the severity of UC of a patient. However, it is very difficult to evaluate the severity of UC objectively because of non-uniform nature of symptoms and large variations in their patterns. To address this, in our previous works, we developed two different approaches in which one is using the image textures, and the other is using CNN (convolutional neural network) to measure and classify objectively the severity of UC presented in optical colonoscopy video frames. But, we found that the image texture based approach could not handle larger number of variations in their patterns, and the CNN based approach could not achieve very high accuracy. In this paper, we improve our CNN based approach in two ways to provide better accuracy for the classification. We add more thorough and essential preprocessing, and generate more classes to accommodate large variations in their patterns. The experimental results show that the proposed preprocessing can improve the overall accuracy of evaluating the severity of UC.
BSM Message and Video Streaming Quality Comparative Analysis Using Wave Short Message Protocol (WSMP)
Vehicular ad-hoc networks (VANETs) are used for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. The IEEE 802.11p/WAVE (Wireless Access in Vehicular Environment) and with WAVE Short Messaging Protocol (WSMP) has been proposed as the standard protocol for designing applications for VANETs. This communication protocol must be thoroughly tested before reliable and efficient applications can be built using its protocols. In this paper, we perform on-road experiments in a variety of scenarios to evaluate the performance of the standard. We use commercial VANET devices with 802.11p/WAVE compliant chipsets for both BSM (basic safety messages) as well as video streaming applications using WSMP as a communication protocol. We show that while the standard performs well for BSM application in lightly loaded conditions, the performance becomes inferior when traffic and other performance metric increases. Furthermore, we also show that the standard is not suitable for video streaming due to the bursty nature of traffic and the bandwidth throttling, which is a major shortcoming for V2X applications.
Mining Biomedical Data for Hidden Relationship Discovery
With an ever-growing number of publications in the biomedical domain, it becomes likely that important implicit connections between individual concepts of biomedical knowledge are overlooked. Literature based discovery (LBD) is in practice for many years to identify plausible associations between previously unrelated concepts. In this paper, we present a new, completely automatic and interactive system that creates a graph-based knowledge base to capture multifaceted complex associations among biomedical concepts. For a given pair of input concepts, our system auto-generates a list of ranked subgraphs uncovering possible previously unnoticed associations based on context information. To rank these subgraphs, we implement a novel ranking method using the context information obtained by performing random walks on the graph. In addition, we enhance the system by training a Neural Network Classifier to output the likelihood of the two concepts being likely related, which provides better insights to the end user.
Parallel Analysis of Aspect-Based Sentiment Summarization from Online Big-Data
Consumer's opinions and sentiments on products can reflect the performance of products in general or in various aspects. Analyzing these data is becoming feasible, considering the availability of immense data and the power of natural language processing. However, retailers have not taken full advantage of online comments. This work is dedicated to a solution for automatically analyzing and summarizing these valuable data at both product and category levels. In this research, a system was developed to retrieve and analyze extensive data from public online resources. A parallel framework was created to make this system extensible and efficient. In this framework, a star topological network was adopted in which each computing unit was assigned to retrieve a fraction of data and to assess sentiment. Finally, the preprocessed data were collected and summarized by the central machine which generates the final result that can be rendered through a web interface. The system was designed to have sound performance, robustness, manageability, extensibility, and accuracy.
Merlin Classifier System
There is a natural tendency for biological systems to change as their environments change. The fittest in the biological systems survive, adapt to their environment, and multiply while the weakest in the environment diminish. There have been attempts in computer science to model the processes of natural selection and survival which occur in biological systems in order to obtain more efficient and effective machine-learning algorithms. Genetic algorithms are the result of these attempts.
The Telecommunications Network Configuration Optimization Problem
The purpose of telecommunication network configuration optimization is to find the best homing relationship between tandems and switches so as to minimize interswitch traffic, or equivalently to maximize intraswitch traffic. Note that, since minimal interswitch traffic implies minimal IMT utilization, communication costs will also be minimal.
An English and Arabic Character Printer
This paper is presented in satisfaction of the requirement for two problems in lieu of thesis which are required for the degree, Master of Science. The two problems are: (1) to provide an electric interface between the M6800 microprocessor and the printer; and (2) to design an Arabic character set and to provide the logic required for its implementation. As it would be artificial and impractical to document these problems separately, a single document here is provided.
Machine Recognition of Hand-Send Morse Code Using the M6800 Microcomputer
This research is the result of an effort to provide real-time machine recognition of hand-send Morse code through the use of the M6800 microcomputer. While the capability to recognize hand-send Morse code messages by machine has been demonstrated before on large scale special purpose computers, on minicomputers, and even on the M6800 microcomputer, the main contribution of this paper is to demonstrate it with relatively understandable hardware and software.
A Report on Control of Access to Stored Information in a Computer Utility
Time-sharing computer systems permit large numbers of users to operate on common sets of data and programs. Since certain parts of these computer resources may be sensitive or proprietary, there exists the risks that information belonging to one user, may, contrary to his intent, become available to other users, and there is the additional risk that outside agencies may infiltrate the system and obtain information. The question naturally arises of protecting one user's stored program and data against unauthorized access by others.
Design and Implementation of a PDP-8 Computer Assembler Executing on the IBM 360/50 Computer
This problem is intended to be an introduction to the design of a software system which translates PDP-8 assembly language source into it's machine-readable object code. This assembler runs on the IBM 360/50. It is assumed that the reader is familiar with the basic PDP-8 assembly language. For the description and use of this assembler the reader is referred to the PAL-III SYMBOLIC ASSEMBLER PROGRAMMING MANUAL from DEC (order number DIGITAL 8-3-5, Digital Equipment Corporation: Maynard, Massachusetts, 1965.). The Second problem of the study concerns the design of a simulator for the PDP-8 computer.
ADA Tasking Facilities for Concurrent and Real-Time Programming
This paper describes multitasking facilities of Ada in concurrent and real-time programming. Synchronization and process communication mechanisms are discussed in detail, also, a new mechanism to solve the scheduling problem is developed. In the concurrent programming aspect, a comparison is made between Ada's rendezvous and Pascal's Monitor concept. In the real-time programming aspect, the differences between the Ada multitasking and the traditional "cyclic executive approaches are contrasted and their associated costs/benefits analyzed.
A Computer Solved Scheduling Problem
The purpose of this paper is to illustrate the use of the computer in solving complex real time scheduling problems. This problem involves the airline industry and is concerned with the local scheduling of security personnel to the gate areas for outgoing flights from one terminal at Dallas-Fort Worth airport. The purpose of this type of program is to enhance personnel efficiency and management control over a large group of people while cutting the cost of lower management.
Text Processing for Thai Characters
The purpose of this project is 1) to create a Thai character set for text processing, 2) to write a text processing program for the character set, and 3) to allow users to create and save the text.
A Comparison of Meansort and Quicksort
The main purpose of this project is to compare a new sorting method- Meansort with its preceding sorting method- Quicksort. Meansort uses the mean value for each key to determine the partition of the file, but Quicksort selects at random. Experiments proved that in some ways Meansort is superior to Quicksort but is still not perfect since it always needs a mean value for each key. This project implements these two methods and determines the situations under which each of these methods outperforms the other.
The Data Structure of a KSAM Key Directory
The purpose of this project is to explore the alternate data structures for a disk file which is currently a preorder binary tree. specifically, the file is the key directory for an implementation of Keyed Sequential Access Method (KSAM) in a mini-computer operating system. A new data structure will be chosen, with the reasons for that choice given, and it will be incorporated into the existing system.
Mini-ADA Compiler Project
The Ada language is one of the most controversial topics in computer science today. Ada was originally designed as a solution to the software maintenance problems encountered by the United States Department of Defense[2], and as a multi-purpose language to be used particularly in an embedded computer system[7]. Never before has a project been undertaken. The Ada language does not simply entail the construction of a new compiler or a new language definition, it is this and a great deal more.
Design and Implementation of a Text Editor Under Music Interactive Operating System
An interactive text editor is a computer program that allows a user to create and revise a target document such as program statements, manuscript text, and numeric data through an online terminal and the computer. It allows text to be modified and corrected many orders of magnitude faster and more easily than would manual correction. The most important characteristic of the text editor is its convenience for the user. Such convenience requires a simple, mnemonic command language which is easy to use and understand.
Multiple Window Editor
This paper is written to present the design purpose and design process of the Multiple Window Editor. Multiple Window Editor is a software which allows the user to edit or view different files or the same file on the screen by the window facilities provided by this software. All the windows can be dynamically created, changed, moved, and destroyed. The main purpose of this program is to improve the programming environment for the users. The design motivations will be introduced through the comparison of the present existing window facilities and the editor components. The design process will be introduced by analyzing the design decision, design tradeoffs and implementation problems.
A Survey of Computer Systems: IBM System/360, 3031, The Decsystem-20, The Univac 1100, and The Cray-1, and The AS/5000
This is a brief survey of some of the popular computer systems. As many features as possible have been covered in order to get an overview of the systems under consideration.
Notes on the SWTPC MP-N Calculator Interface and the Calc-1 Program
This interface was bought to perform floating-point arithmetic and for its function capabilities such as SIN, COS, and e^x. My application required an integer truncation function that is not performed by this calculator, so i wrote a small assembly language subroutine to do it. A potentially irritating problem is that the calculator chip does not automatically convert to scientific notation if the numbers become too big to display in floating point. The control program must keep track of the display mode.
VISOR (Variable Interval Schedule Of Reinforcement) System Documentation
This program will be used in operant behavior research to monitor and record responses and trigger and record reinforcements on a variable reinforcement (VI) schedule. The original application of this program will be the servicing of several rat cages simultaneously. The response will be the pressing of a metal bar in the cage, the reinforcement will be the triggering of a feeding mechanism which disperses a food pellet into the cage. The subsequent applications of this program are not limited, in that the actual response and reinforcement devices and the subject type are all treated indifferently by the program.
The NTSU School of Music Practice Room Scheduling System
This is a report concerning the project I completed for my 590 (special problem) credit. The subject of this project was a system for interactive practice room scheduling by music students at NTSU. This system was created in the fall semester of 1982 as a class project for software Development (CSCI 553) with Dr. Irby. The system was not completely finished, and I received permission from Dr. Irby to finish it and help implement its use at the Music department. I was able to observe three usages of the system: Spring, Summer I, and Summer II semesters of 1983. This report details the problems encountered during each of these usages, and changes made to the system due to them. Results of a first-use survey, under documentation, and complete final code listings were also included.
FORTRAN Graphics Library
The objective of this work is to help the faculty, staffs and students of NTSU to use the CalComp plotting facility very easily. Therefore, this work is written in such a step by step and self-explanatory way to help the reader to understand and grasp the essential technique of the computer plotting. Each subroutine illustrated in this work has been run and checked by our NTSU computer-CalComp plotting facility; the results of sample programs and illustrated graphs are believed to be very useful to understand each individual subroutine. Basically, software packages are stored in the magnetic disk of the IBM 360 computer as the standard graphic subroutines. These subroutines were written in FORTRAN IV. The user can write the driving program to call these subroutines and also inputs the desire data to the computer for computation. The results of computation will be outputed and stored in the magnetic tape.
PILOT for the Apple II Microcomputer
PILOT (Programmed Inquiry, Learning or Teaching) is a simple, conversational language developed in 1969 by John A. Starkweather at the University of California Medical Center in San Francisco. Originally designed for computer assisted instructional needs, PILOT also has been effectively used as an introductory computer language. The PILOT system developed for the Apple II microcomputer consists of two programs, PILOT EDITOR and PILOT DRIVER, which are written in Applesoft and which use the Apple II disk operating system. The PILOT system was designed to facilitate easy authoring and execution of programs written in an extended version of the PILOT language. Due to the memory requirements of the programs and the Apple II disk operating system, the PILOT system described here should be executed on a machine with at least 32k bytes of random access memory.
Design and Implementation of a Parser for the DBase II Query Language
In this paper the DBase II query language of an RDBMS for personal computers is discussed. Other languages will be provided by large and sophisticated DBMS will not be discussed here. The reason for selecting the DBase II query language for discussion are as follows: 1. It is a simple language that can be learned easily [TOWN 84, DINE 84]. Within a short period, users can learn all of the facilities and manage the system very well. 2. It is a language suitable for interactive programming and execution like BASIC. 3. It provides adequate facilities for a small data base system and serves as an introductory guide for more sophisticated systems.
Development of a Text Formatted Under VAX/VMS Operating System
No matter how extended the use of the computer is, the printed document is still the primary medium for the presentation information, and will continue to be for some time. The use of computing facilities for preparation and production of the document is becoming as prevalent as their use for numeric computation. Commercially, document preparation systems are now a standard facility at research institution, and they have become quite common on each computer program. A conventional document preparation system usually contains two parts: a text editor used to create, enter, update, and maintain the text and control words that comprise the document in its "input" form, and a text formatter used to process that input and produce the final document.
Triangle: A Teaching Program of High School Geometry
Among the early applications of computers, one can find frequent mention of intelligent instructional systems. Such intelligent instructional systems represent a new generation of learner-based computer aided instruction, preceded in time by the original frame-based systems and an intervening generation of expert-based CAI. The history of CAI is characterized by three generations: Frame-based CAI, Expert-based CAI and Learner-based CAI.
A Method for Applying Scientific Subroutine Package in Microprocessor
The scientific subroutine package is one of the most important parts of the software for the scientific industry. By now, most big computers have scientific packages, but applying such a software package in microprocessors requires consideration of the microprocessor's facilities, such as limited main memory, slow execution time, and only a few small registers. In any scientific package, the trigonometric functions are the ones more widely used. This paper discusses a method for implementing several trigonometric function programs in a scientific package in microprocessors. These programs will contain routines for computing sin, cos, tan, and cot of any angle within the range of (-360°,+360°).
Macro - Preprocessor for 6809 Cross Assembler
It is frequently considered to be apparent two stages during assembly time. The first is the preprocessor stage in which a single instruction called the micro instruction is replaced with the sequence of instructions called the macro definition. The second is the processor stage in which the output from the first stage is assembled into machine language instructions for a particular computer. This paper descibes the first one which is macro-preprocessor stage.
Initial Research for the Development or Purchase of a Computerized Synthesizer For Use as a Composer's Aid
The author's primary goal is to begin research leading ot the attainment of a low cost computer/music system which will allow the composer to write polyphonic music of up to eight voices into a computer through a terminal, and have the music played back by means of computer synthesized sound or by means of a conventional synthesizer controlled by a computer via digital-to-analog converters. The goal system will allow the composer to retreat and hear his product objectively as the painter steps back to review his canvas.
Field Programmable Devices and Reconfigurable Computing
The motivation behind this research has been the idea of the capability of the computing device to dynamically reconfigure itself. The goal of this work is to measure the computational power of reconfigurable machines rather in an abstract manner by proposing a model the FPGAs abstract computing machines. Modeling FPGAs in terms of Automata Theory would give a base to answer more fundamental questions about the capabilities and possible answers. If a Finite State Machine (FSM) or a Turing Machine (TM) has the capability of reconfiguring its finite control, does this ability give the abstract computing device new computational power. In other words is a reconfigurable FSM, TM or a Cellular Automata more powerful than their corresponding non-configurable versions?
Extracting Temporally-Anchored Knowledge from Tweets
Twitter has quickly become one of the most popular social media sites. It has 313 million monthly active users, and 500 million tweets are published daily. With the massive number of tweets, Twitter users share information about a location along with the temporal awareness. In this work, I focus on tweets where author of the tweets exclusively mentions a location in the tweet. Natural language processing systems can leverage wide range of information from the tweets to build applications like recommender systems that predict the location of the author. This kind of system can be used to increase the visibility of the targeted audience and can also provide recommendations interesting places to visit, hotels to stay, restaurants to eat, targeted on-line advertising, and co-traveler matching based on the temporal information extracted from a tweet. In this work I determine if the author of the tweet is present in the mentioned location of the tweet. I also determine if the author is present in the location before tweeting, while tweeting, or after tweeting. I introduce 5 temporal tags (before the tweet but > 24 hours; before the tweet but < 24 hours; during the tweet is posted; after the tweet is posted but < 24 hours; and after the tweet is posted but > 24 hours). The major contributions of this paper are: (1) creation of a corpus of 1062 tweets containing 1200 location named entities, containing annotations whether author of a tweet is or is not located in the location he tweets about with respect to 5 temporal tags; (2) detailed corpus analysis including real annotation examples and label distributions per temporal tag; (3) detailed inter-annotator agreements, including Cohen's kappa, Krippendorff's alpha and confusion matrices per temporal tag; (4) label distributions and analysis; and (5) supervised learning experiments, along with …
Detecting Component Failures and Critical Components in Safety Critical Embedded Systems using Fault Tree Analysis
Component failures can result in catastrophic behaviors in safety critical embedded systems, sometimes resulting in loss of life. Component failures can be treated as off nominal behaviors (ONBs) with respect to the components and sub systems involved in an embedded system. A lot of research is being carried out to tackle the problem of ONBs. These approaches are mainly focused on the states (i.e., desired and undesired states of a system at a given point of time to detect ONBs). In this paper, an approach is discussed to detect component failures and critical components of an embedded system. The approach is based on fault tree analysis (FTA), applied to the requirements specification of embedded systems at design time to find out the relationship between individual component failures and overall system failure. FTA helps in determining both qualitative and quantitative relationship between component failures and system failure. Analyzing the system at design time helps in detecting component failures and critical components and helps in devising strategies to mitigate component failures at design time and improve overall safety and reliability of a system.
Mobile-Based Smart Auscultation
In developing countries, acute respiratory infections (ARIs) are responsible for two million deaths per year. Most victims are children who are less than 5 years old. Pneumonia kills 5000 children per day. The statistics for cardiovascular diseases (CVDs) are even more alarming. According to a 2009 report from the World Health Organization (WHO), CVDs kill 17 million people per year. In many resource-poor parts of the world such as India and China, many people are unable to access cardiologists, pulmonologists, and other specialists. Hence, low skilled health professionals are responsible for screening people for ARIs and CVDs in these areas. For example, in the rural areas of the Philippines, there is only one doctor for every 10,000 people. By contrast, the United States has one doctor for every 500 Americans. Due to advances in technology, it is now possible to use a smartphone for audio recording, signal processing, and machine learning. In my thesis, I have developed an Android application named Smart Auscultation. Auscultation is a process in which physicians listen to heart and lung sounds to diagnose disorders. Cardiologists spend years mastering this skill. The Smart Auscultation application is capable of recording and classifying heart sounds, and can be used by public or clinical health workers. This application can detect abnormal heart sounds with up to 92-98% accuracy. In addition, the application can record, but not yet classify, lung sounds. This application will be able to help save thousands of lives by allowing anyone to identify abnormal heart and lung sounds.
Object Recognition Using Scale-Invariant Chordiogram
This thesis describes an approach for object recognition using the chordiogram shape-based descriptor. Global shape representations are highly susceptible to clutter generated due to the background or other irrelevant objects in real-world images. To overcome the problem, we aim to extract precise object shape using superpixel segmentation, perceptual grouping, and connected components. The employed shape descriptor chordiogram is based on geometric relationships of chords generated from the pairs of boundary points of an object. The chordiogram descriptor applies holistic properties of the shape and also proven suitable for object detection and digit recognition mechanisms. Additionally, it is translation invariant and robust to shape deformations. In spite of such excellent properties, chordiogram is not scale-invariant. To this end, we propose scale invariant chordiogram descriptors and intend to achieve a similar performance before and after applying scale invariance. Our experiments show that we achieve similar performance with and without scale invariance for silhouettes and real world object images. We also show experiments at different scales to confirm that we obtain scale invariance for chordiogram.
Extracting Useful Information from Social Media during Disaster Events
In recent years, social media platforms such as Twitter and Facebook have emerged as effective tools for broadcasting messages worldwide during disaster events. With millions of messages posted through these services during such events, it has become imperative to identify valuable information that can help the emergency responders to develop effective relief efforts and aid victims. Many studies implied that the role of social media during disasters is invaluable and can be incorporated into emergency decision-making process. However, due to the "big data" nature of social media, it is very labor-intensive to employ human resources to sift through social media posts and categorize/classify them as useful information. Hence, there is a growing need for machine intelligence to automate the process of extracting useful information from the social media data during disaster events. This dissertation addresses the following questions: In a social media stream of messages, what is the useful information to be extracted that can help emergency response organizations to become more situationally aware during and following a disaster? What are the features (or patterns) that can contribute to automatically identifying messages that are useful during disasters? We explored a wide variety of features in conjunction with supervised learning algorithms to automatically identify messages that are useful during disaster events. The feature design includes sentiment features to extract the geo-mapped sentiment expressed in tweets, as well as tweet-content and user detail features to predict the likelihood of the information contained in a tweet to be quickly spread in the network. Further experimentation is carried out to see how these features help in identifying the informative tweets and filter out those tweets that are conversational in nature.
Brain Computer Interface (BCI) Applications: Privacy Threats and Countermeasures
In recent years, brain computer interfaces (BCIs) have gained popularity in non-medical domains such as the gaming, entertainment, personal health, and marketing industries. A growing number of companies offer various inexpensive consumer grade BCIs and some of these companies have recently introduced the concept of BCI "App stores" in order to facilitate the expansion of BCI applications and provide software development kits (SDKs) for other developers to create new applications for their devices. The BCI applications access to users' unique brainwave signals, which consequently allows them to make inferences about users' thoughts and mental processes. Since there are no specific standards that govern the development of BCI applications, its users are at the risk of privacy breaches. In this work, we perform first comprehensive analysis of BCI App stores including software development kits (SDKs), application programming interfaces (APIs), and BCI applications w.r.t privacy issues. The goal is to understand the way brainwave signals are handled by BCI applications and what threats to the privacy of users exist. Our findings show that most applications have unrestricted access to users' brainwave signals and can easily extract private information about their users without them even noticing. We discuss potential privacy threats posed by current practices used in BCI App stores and then describe some countermeasures that could be used to mitigate the privacy threats. Also, develop a prototype which gives the BCI app users a choice to restrict their brain signal dynamically.
Automated GUI Tests Generation for Android Apps Using Q-learning
Mobile applications are growing in popularity and pose new problems in the area of software testing. In particular, mobile applications heavily depend upon user interactions and a dynamically changing environment of system events. In this thesis, we focus on user-driven events and use Q-learning, a reinforcement machine learning algorithm, to generate tests for Android applications under test (AUT). We implement a framework that automates the generation of GUI test cases by using our Q-learning approach and compare it to a uniform random (UR) implementation. A novel feature of our approach is that we generate user-driven event sequences through the GUI, without the source code or the model of the AUT. Hence, considerable amount of cost and time are saved by avoiding the need for model generation for generating the tests. Our results show that the systematic path exploration used by Q-learning results in higher average code coverage in comparison to the uniform random approach.
Back to Top of Screen